Subscribe to DSC Newsletter

Data Scientist communities have their own complex jargon; multivariate regression models, Big data engineering, Hadoop, Map Reduce, Deep Learning etc. But, unfortunately businesses do not seem to care about how complex the term is or how impressive the math is! They want the results explained in non-tech terms.

While working on Big Data & planning to implement it for the benefit of business, it is very important to explain the insights & valuable knowledge in a way that non-technical business user can actually understand.

Here is my recent experience while working on a project for one of the largest food retailers. The goal of this project was how incentivisation would help improve their overall profits.

After an extensive and impressive study, our team came up with a collection of (what they thought) elegantly done slides. They discussed deeply about variance inflation factors, Akaike information criterion that would scare even seasoned practitioners of the art.

Now the client did not have a clue of what was going on during the presentation and rushed and escalated to me. I had to work several days De-technifying the slides! And make them business friendly

More often than not, I notice that I spend 50% of the time processing and cleaning the data and 20-25% of the time De-technifying the results and tell stories. Interestingly, while I find enough doers, the story tellers who understand the subject and business at appropriate depth are rare.

Unfortunately, this skill is missing in traditional MBAs & Managers as this is not a peripheral exercise of language. A fairly deep understanding of Data Science must be coupled with a even deeper research of the client organization.

Need to rush now. But, I shall talk about my thoughts on how to solve this problem on a later post.

Contd

Article idea & guidance by - Dr Dakshina Murthy Kolluru

Script, Design & Edited by - Suman Malekani

Views: 3703

Comment

You need to be a member of Data Science Central to add comments!

Join Data Science Central

Comment by INSOFE on February 2, 2015 at 11:51pm

Sione Palu 

Hahaha the image is just for a hysterical representation.

Comment by Sione Palu on February 2, 2015 at 11:21pm

I recognized the formulas in that image in the post as those from Quantum Mechanics, especially the Coulomb energy curve and the particle location probability distribution diagram, lol!!!  Anyway, some of those Physics' concepts have found their way to machine learning & big data, like Boltzman-machine.

Comment by Robert Bagley on February 2, 2015 at 9:30am

This concept is absolutely critical, and I'm glad we have a well-written reminder here. When presenting to a technical audience of other Data Scientists, the presentation can be in-depth, can discuss complex variable relationships, etc. However, based on my own experiences working within large clients, the Business Sponsor role can better participate in the conversation and will be more engaged when the content is boiled down in his/her own terms - and those terms can be dramatically different from one engagement to the next. In a general sense, you have to know your audience.

Follow Us

Videos

  • Add Videos
  • View All

Resources

© 2017   Data Science Central   Powered by

Badges  |  Report an Issue  |  Privacy Policy  |  Terms of Service